Body mass index and the risk of Parkinson disease

Epidemiologic Risk and Prevention and Interventions in Parkinson Disease: From a Nutrition-Based Perspective

Parkinson disease (PD) is a prevalent neurodegenerative disorder associated with aging. Current treatments for PD primarily focus on alleviating symptoms rather than altering the progression of the disease. The sporadic form of PD, which accounts for most cases, is thought to arise from a complex interaction between genetic predispositions and environmental factors. This review aimed to examine epidemiologic evidence regarding nutrition-related exposure factors and their associations with risk of developing PD. We proposed a tentative conclusion for each factor based on the available evidence. These associations may vary by gender and depend on dietary intake patterns and adherence. We also reviewed clinical trials on nutrition-related interventions for PD symptoms and progression. Future clinical trials may benefit from combining nutrition factors in intervention and testing within single-gender cohorts or subgroups defined by epidemiologic outcomes.

Large-scale proteomic analyses of incident Parkinson's disease reveal new pathophysiological insights and potential biomarkers

The early pathophysiology of Parkinson's disease (PD) is poorly understood. We analyzed 2,920 Olink-measured plasma proteins in 51,804 UK Biobank participants, identifying 859 incident PD cases after 14.45 years. We found 38 PD-related proteins, with six of the top ten validated in the Parkinson's Progression Markers Initiative (PPMI) cohort. ITGAV, HNMT and ITGAM showed consistent significant association (hazard ratio: 0.11-0.57, P = 6.90 × 10-24 to 2.10 × 10-11). Lipid metabolism dysfunction was evident 15 years before PD onset, and levels of BAG3, HPGDS, ITGAV and PEPD continuously decreased before diagnosis. These proteins were linked to prodromal symptoms and brain measures. Mendelian randomization suggested ITGAM and EGFR as potential causes of PD. A predictive model using machine learning combined the top 16 proteins and demographics, achieving high accuracy for 5-year (area under the curve (AUC) = 0.887) and over-5-year PD prediction (AUC = 0.816), outperforming demographic-only models. It was externally validated in PPMI (AUC = 0.802). Our findings reveal early peripheral pathophysiological changes in PD crucial for developing early biomarkers and precision therapies.

Association and biological pathways between metabolic syndrome and incident Parkinson's disease: A prospective cohort study of 289,150 participants

The relationship between metabolic syndrome (MetS) and Parkinson's disease (PD) remains uncertain due to inconsistent findings in previous studies. This prospective cohort study investigated the association between MetS and PD risk, along with potential biological mechanisms, using data from 289,150 PD-free participants in the UK Biobank. MetS was defined by the presence of at least three of the following components, while preMetS included one or two: increased waist circumference, elevated triglycerides (TG), high blood pressure (BP), elevated HbA1c, or reduced high-density lipoprotein cholesterol (HDL-C). Cox proportional hazards models were utilized to assess the risk of PD, and mediation analyses explored the role of blood biomarkers. Over a median follow-up of 13.1 years, 1682 participants developed PD. PreMetS (HR: 1.24, 95 % CI: 1.02-1.51, P = 0.028) and MetS (HR: 1.32, 95 % CI: 1.08-1.61, P = 0.008) were associated with an increased PD risk, with Kaplan-Meier analysis showing risk escalation with more MetS components. Among individual MetS components, increased waist circumference, elevated HbA1c, and reduced HDL-C were significantly associated with higher PD risk, while elevated TG and BP showed no significant association. Mediation analysis indicated that biomarkers of liver function (alkaline phosphatase) and kidney function (cystatin C) partially mediated the MetS-PD relationship. These findings highlight a significant link between MetS and higher PD risk, with possible mediation through specific blood biomarkers, though temporal ambiguity warrants cautious interpretation.

Associations of the Life's Essential 8 with Parkinson's disease: a population-based study

Background

Parkinson's disease (PD) is a progressive neurodegenerative disorder with increasing global prevalence. This study investigated the association between the American Heart Association's Life's Essential 8 (LE8) and PD prevalence using a large, nationally representative database.

Methods

We analyzed data from 18,277 participants aged 40 years and older from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. LE8 scores were calculated based on diet, physical activity, nicotine exposure, sleep, body mass index, blood lipids, blood glucose, and blood pressure. PD cases were identified through self-reported anti-PD medication use. Multivariate logistic regression models were employed to examine the association between LE8 and PD prevalence, adjusting for various demographic and clinical factors. In addition, we performed restricted cubic splines (RCS), subgroup analyses, and weighted quantile sum (WQS) regression to verify the robustness of the study results.

Results

The prevalence of PD was 1.3% in the study population. After full adjustment, individuals with moderate (50-79) and high (80-100) LE8 scores showed lower odds of PD compared to those with low (0-49) scores (OR 0.53, 95% CI 0.29-0.97 and OR 0.43, 95% CI 0.17-1.04, respectively; p for trend <0.05). A dose-response relationship was observed between LE8 scores and PD prevalence. WQS regression identified dietary factors and glycemic health as the main contributors to the inverse association between LE8 and PD.

Conclusion

Our findings suggest a significant inverse association between Life's Essential 8 (LE8) and PD prevalence, with dietary factors and glycemic health emerging as the most influential components.

Obesity and the development of Parkinson's disease within the Framingham Heart study cohort

Objective

To determine the role of obesity in the development of Parkinson's disease (PD).

Background

Obesity has been reported to be both a risk factor for PD, as well as potentially protective. The Framingham Heart Study (FHS) is a multigenerational longitudinal cohort study that was started in 1948, which is well-known for its cardiovascular health studies. In this study, we utilized the extensive cardiovascular and neurological data to determine if obesity contributes to the risk of the development of PD.

Methods

Participants in the FHS Original and Offspring cohorts were included in this study. Controls were selected based on sex and age at baseline examination, 1:10. Cox proportional hazard regression models were used, adjusting for age and sex. PD case status was determined utilizing prior medical and neurological examination data, Framingham Heart Study examinations, and self-report data by a panel of movement disorders neurologists using the UK Brain Bank Criteria (UKBB) and other supporting clinical details after being flagged for review by FHS neurologists. We used p < 0.05 for significance.

Results

Accounting for missing covariate data, this study included 117 participants with PD, with 1170 controls. We found that higher BMI was associated with lower PD risk, with participants with BMI 25 kg/m2 to 30 kg/m2 having HR of 0.66 (CI 0.44-0.98; p = 0.04) and BMI >= 30 kg/m2 having HR 0.47 (CI 0.27-0.84; p = 0.01). When the overweight and obese BMI groups were combined, we noted a more robust association, with combined HR of 0.67 (0.41-0.86; p = 0.01).

Conclusions

Obesity during mid-life potentially reduces the risk of developing PD; however, additional studies are needed to further explore this association.

Metabolic profiling reveals circulating biomarkers associated with incident and prevalent Parkinson's disease

The metabolic profile predating the onset of Parkinson's disease (PD) remains unclear. We aim to investigate the metabolites associated with incident and prevalent PD and their predictive values in the UK Biobank participants with metabolomics and genetic data at the baseline. A panel of 249 metabolites was quantified using a nuclear magnetic resonance analytical platform. PD was ascertained by self-reported history, hospital admission records and death registers. Cox proportional hazard models and logistic regression models were used to investigate the associations between metabolites and incident and prevalent PD, respectively. Area under receiver operating characteristics curves (AUC) were used to estimate the predictive values of models for future PD. Among 109,790 participants without PD at the baseline, 639 (0.58%) individuals developed PD after one year from the baseline during a median follow-up period of 12.2 years. Sixty-eight metabolites were associated with incident PD at nominal significance (P < 0.05), spanning lipids, lipid constituent of lipoprotein subclasses and ratios of lipid constituents. After multiple testing corrections (P < 9 × 10-4), polyunsaturated fatty acids (PUFA) and omega-6 fatty acids remained significantly associated with incident PD, and PUFA was shared by incident and prevalent PD. Additionally, 14 metabolites were exclusively associated with prevalent PD, including amino acids, fatty acids, several lipoprotein subclasses and ratios of lipids. Adding these metabolites to the conventional risk factors yielded a comparable predictive performance to the risk-factor-based model (AUC = 0.766 vs AUC = 0.768, P = 0.145). Our findings suggested metabolic profiles provided additional knowledge to understand different pathways related to PD before and after its onset.

Association between a body shape index and Parkinson's disease: A large cross-sectional study from NHANES

Objective

To further evaluate the connection between obesity and Parkinson's disease, we utilized A body shape index which normalizes waist circumference for Body mass index. Derived from the National Health and Nutrition Examination Survey.

Methods

Based on National Health and Nutrition Examination Survey data from 2005 to 2018, this study included 31,933 adult participants in total. First, all the participants were divided into the Parkinson's disease group and non-Parkinson's disease group, respectively. Next, according to their quartiles of A body shape index levels, they were further classified into Q1 group (0.058-0.077), Q2 group (0.078-0.081), Q3 group (0.082-0.084), and Q4 group (0.085-0.117). A body shape index was the primary exposure, while Parkinson's disease was the primary outcome. A body shape index is defined by waist circumference divided by Body mass index2/3 × height1/2, and the expected value of waist circumference based on height and weight derived empirically from National Health and Nutrition Examination Survey. Consequently, A body shape index and Parkinson's disease were analyzed through multifactor logistic regression.

Results

According to the unadjusted multivariate logistic analysis, the Q4 group had a greater likelihood of acquiring Parkinson's disease than the Q1 group [OR = 4.519, 95% CI: 3.094-6.600; P < 0.001]. After adjusting the demographic variables such as age, sex, and race, Q4 group was at a higher risk of Parkinson's disease acquisition than Q1 [OR (95% CI): 2.677 (1.774-4.038); P < 0.001]. Compared with Q1 group, the male participants were in a greater chance of getting Parkinson's disease than female participants in Q4 group, as shown by subgroup analysis by gender [male vs. female: OR = 6.563 (3.289-13.098) vs. OR = 3.827 (2.398-6.108); Interaction P-value<0.001].

Conclusions

There is a non-linear positive correlation between the adult A body shape index and the risk of Parkinson's disease. Adults are at a greater risk of getting Parkinson's disease as A body shape index rises, and the link is particularly strong among men aged 20 to 59.

Differential effects of cholesterol levels on cognition according to body mass index in Parkinson's disease

BACKGROUND

Cholesterol is an essential component of the neuronal cell membrane and is crucial for neuronal function; however, the role of cholesterol levels in Parkinson's disease (PD) is debatable. This study investigated the complex relationship between total cholesterol (TC) levels, body mass index (BMI), and cognition in patients with PD.

METHODS

This study included 321 drug-naïve patients with PD who underwent dopamine transporter (DAT) imaging and baseline neuropsychological tests. Multivariate linear regression and Cox regression models were used to investigate the effect of TC levels on the composite score of each cognitive domain and dementia conversion after adjusting for covariates, respectively. Interaction analyses were performed to examine the interaction effect between TC levels and BMI on baseline cognition and dementia conversion.

RESULTS

TC levels and cognition showed no significant relationship after adjusting for potential confounders. A significant interaction effect between TC levels and BMI was observed in frontal/executive function and dementia conversion. Further analyses showed that TC levels were positively associated with frontal/executive function in the under-/normal weight group (β = 0.205, p = 0.013), whereas a negative relationship existed between TC levels and frontal/executive function in the obese group (β =  - 0.213, p = 0.017). Cox regression analyses also showed the differential effects of TC levels on dementia conversion according to BMI (under-/normal weight group: hazard ratio [HR] = 0.550, p = 0.013; obese group: HR = 2.085, p = 0.014).

CONCLUSIONS

This study suggests a cross-over interaction between TC levels and BMI on cognitive symptoms in PD.

Air Pollutants and Risk of Parkinson's Disease among Women in the Sister Study

BACKGROUND

Air pollutants may contribute to the development of Parkinson's disease (PD), but empirical evidence is limited and inconsistent.

OBJECTIVES

This study aimed to prospectively investigate the associations of PD with ambient exposures to fine particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) and nitrogen dioxide (NO 2 ).

METHODS

We analyzed data from 47,108 US women from the Sister Study, enrolled from 2003-2009 (35-80 years of age) and followed through 2018. Exposures of interest included address-level ambient PM 2.5 and NO 2 in 2009 and their cumulative averages from 2009 to PD diagnosis with varying lag-years. The primary outcome was PD diagnosis between 2009 and 2018 (n = 163 ). We used multivariable Cox proportional hazards and time-varying Cox models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

NO 2 exposure in 2009 was associated with PD risk in a dose-response manner. The HR and 95% CI were 1.22 (95% CI: 1.03, 1.46) for one interquartile [4.8 parts per billion (ppb)] increment in NO 2 , adjusting for age, race and ethnicity, education, smoking status, alcohol drinking, caffeine intake, body mass index, physical activity, census region, residential area type, area deprivation index (ADI), and self-reported health status. The association was confirmed in secondary analyses with time-varying averaged cumulative exposures. For example, the multivariable adjusted HR for PD per 4.8   ppb increment in NO 2 was 1.25 (95% CI: 1.05, 1.50) in the 2-year lag analysis using cumulative average exposure. Post hoc subgroup analyses overall confirmed the association. However, statistical interaction analyses found that the positive association of NO 2 with PD risk was limited to women in urban, rural, and small town areas and women with ≥ 50 th percentile ADI but not among women from suburban areas or areas with < 50 th percentile ADI. In contrast, PM 2.5 exposure was not associated with PD risk with the possible exception for women from the Midwest region of the US (HR interquartile -range = 2.49 , 95% CI: 1.20, 5.14) but not in other census regions.

DISCUSSION

In this nationwide cohort of US women, higher level exposure to ambient NO 2 is associated with a greater risk of PD. This finding needs to be independently confirmed and the underlying mechanisms warrant further investigation. https://doi.org/10.1289/EHP13009.

Association Between Body Mass Index Changes and All-Cause Mortality in Parkinson's Disease

Background

Whether body weight changes are associated with Parkinson's disease (PD) mortality remains uncertain.

Objective

To investigate the association between changes in body mass index (BMI) and all-cause mortality in patients with PD.

Methods

This nationwide cohort study enrolled 20,703 individuals with new-onset PD (ICD-10 code: G20 and a rare intractable disease registration code: V124) who underwent health screening program by the Korean National Health Insurance Service within two years from pre- and post-PD diagnosis. We identified nine BMI change groups based on three BMI status: underweight (BMI < 18.5 kg/m2), normal or overweight (18.5 kg/m2≤BMI < 25 kg/m2), and obese (BMI≥25 kg/m2).

Results

Of 20,703 individuals, 3,789 (18.0%) died during the follow-up period. Excessive weight loss to underweight in the obese group (hazard ratio [HR] = 3.36, 95% CI:1.60-7.08), weight loss in the normal to overweight group (HR = 2.04, 95% CI:1.75-2.39), sustained underweight status (HR = 2.05, 95% CI:1.67-2.52), and weight gain from underweight to normal or overweight (HR = 1.52, 95% CI:1.15-2.02) were associated with increased mortality. Sustained obese status (HR = 0.80, 95% CI:0.74-0.87) and weight gain in the normal to overweight group (HR = 0.82, 95% CI:0.71-0.95) were associated with reduced mortality.

Conclusions

We found that BMI change at diagnosis was associated with mortality in patients with PD. Specifically, being underweight either before or after diagnosis as well as experiencing weight loss, were associated with increased mortality. These findings provide valuable insights for weight management planning in PD, highlighting the importance of individualized approach that consider pre-diagnosis BMI.

Recent research progress on metabolic syndrome and risk of Parkinson's disease

Parkinson's disease (PD) is one of the most widespread neurodegenerative diseases. PD is associated with progressive loss of substantia nigra dopaminergic neurons, including various motor symptoms (e.g., bradykinesia, rigidity, and resting tremor), as well as non-motor symptoms (e.g., cognitive impairment, constipation, fatigue, sleep disturbance, and depression). PD involves multiple biological processes, including mitochondrial or lysosomal dysfunction, oxidative stress, insulin resistance, and neuroinflammation. Metabolic syndrome (MetS), a collection of numerous connected cerebral cardiovascular conditions, is a common and growing public health problem associated with many chronic diseases worldwide. MetS components include central/abdominal obesity, systemic hypertension, diabetes, and atherogenic dyslipidemia. MetS and PD share multiple pathophysiological processes, including insulin resistance, oxidative stress, and chronic inflammation. In recent years, MetS has been linked to an increased risk of PD, according to studies; however, the specific mechanism remains unclear. Researchers also found that some related metabolic therapies are potential therapeutic strategies to prevent and improve PD. This article reviews the epidemiological relationship between components of MetS and the risk of PD and discusses the potentially relevant mechanisms and recent progress of MetS as a risk factor for PD. Furthermore, we conclude that MetS-related therapies are beneficial for the prevention and treatment of PD.

Incidence of Parkinson's disease and modifiable risk factors in Korean population: A longitudinal follow-up study of a nationwide cohort

Introduction

We aimed to investigate the incidence of Parkinson's disease (PD) by age and year for each sex as well as the modifiable risk factors for PD. Using data from the Korean National Health Insurance Service, 938,635 PD and dementia-free participants aged ≥40 years who underwent general health examinations were followed to December 2019.

Methods

We analyzed the PD incidence rates according to age, year and sex. To investigate the modifiable risk factors for PD, we used the Cox regression model. Additionally, we calculated the population-attributable fraction to measure the impact of the risk factors on PD.

Results

During follow-up, 9,924 of the 938,635 (1.1%) participants developed PD. The incidence of PD increased continuously from 2007 to 2018, reaching 1.34 per 1,000 person-years in 2018. The incidence of PD also increases with age, up to 80 y. Presence of hypertension (SHR = 1.09, 95% CI 1.05 to 1.14), diabetes (SHR = 1.24, 95% CI 1.17 to 1.31), dyslipidemia (SHR = 1.12, 95% CI 1.07 to 1.18), ischemic stroke (SHR = 1.26, 95% CI 1.17 to 1.36), hemorrhagic stroke (SHR = 1.26, 95% CI 1.08 to 1.47), ischemic heart disease (SHR = 1.09, 95% CI 1.02 to 1.17), depression (SHR = 1.61, 95% CI 1.53 to 1.69), osteoporosis (SHR = 1.24, 95% CI 1.18 to 1.30), and obesity (SHR = 1.06, 95% CI 1.01 to 1.10) were independently associated with a higher risk for PD.

Discussion

Our results highlight the effect of modifiable risk factors for PD in the Korean population, which will help establish health care policies to prevent the development of PD.

AT1 receptor autoantibodies mediate effects of metabolic syndrome on dopaminergic vulnerability

The metabolic syndrome has been associated to chronic peripheral inflammation and related with neuroinflammation and neurodegeneration, including Parkinson's disease. However, the responsible mechanisms are unclear. Previous studies have involved the brain renin-angiotensin system in progression of Parkinson's disease and the angiotensin receptor type 1 (AT1) has been recently revealed as a major marker of dopaminergic vulnerability in humans. Dysregulation of tissue renin-angiotensin system is a key common mechanism for all major components of metabolic syndrome. Circulating AT1 agonistic autoantibodies have been observed in several inflammation-related peripheral processes, and activation of AT1 receptors of endothelial cells, dopaminergic neurons and glial cells have been observed to disrupt endothelial blood -brain barrier and induce neurodegeneration, respectively. Using a rat model, we observed that metabolic syndrome induces overactivity of nigral pro-inflammatory renin-angiotensin system axis, leading to increase in oxidative stress and neuroinflammation and enhancing dopaminergic neurodegeneration, which was inhibited by treatment with AT1 receptor blockers (ARBs). In rats, metabolic syndrome induced the increase in circulating levels of LIGHT and other major pro-inflammatory cytokines, and 27-hydroxycholesterol. Furthermore, the rats showed a significant increase in serum levels of proinflammatory AT1 and angiotensin converting enzyme 2 (ACE2) autoantibodies, which correlated with levels of several metabolic syndrome parameters. We also found AT1 and ACE2 autoantibodies in the CSF of these rats. Effects of circulating autoantibodies were confirmed by chronic infusion of AT1 autoantibodies, which induced blood-brain barrier disruption, an increase in the pro-inflammatory renin-angiotensin system activity in the substantia nigra and a significant enhancement in dopaminergic neuron death in two different rat models of Parkinson's disease. Observations in the rat models, were analyzed in a cohort of parkinsonian and non-parkinsonian patients with or without metabolic syndrome. Non-parkinsonian patients with metabolic syndrome showed significantly higher levels of AT1 autoantibodies than non-parkinsonian patients without metabolic syndrome. However, there was no significant difference between parkinsonian patients with metabolic syndrome or without metabolic syndrome, which showed higher levels of AT1 autoantibodies than non-parkinsonian controls. This is consistent with our recent studies, showing significant increase of AT1 and ACE2 autoantibodies in parkinsonian patients, which was related to dopaminergic degeneration and neuroinflammation. Altogether may lead to a vicious circle enhancing the progression of the disease that may be inhibited by strategies against production of these autoantibodies or AT1 receptor blockers (ARBs).

Body Mass Index, Abdominal Adiposity, and Incidence of Parkinson Disease in French Women From the E3N Cohort Study

BACKGROUND AND OBJECTIVES

Previous studies on the relationship between body mass index (BMI) and Parkinson disease (PD) provided inconsistent results, likely due to reverse causation explained by weight loss during the prodromal phase. We examined the association of BMI and abdominal adiposity with PD incidence using lagged analyses to address the potential for reverse causation and compared BMI trajectories in patients before diagnosis and matched controls.

METHODS

We used data from the E3N cohort study of French women with a 29-year follow-up (1990-2018). BMI (kg/m²) was computed based on self-reported weight and height up to 11 times; up to 6 waist circumference (WC) and hip circumference measures were available. PD diagnoses were validated based on medical records and drug claim databases. Multivariable time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs according to BMI categories (underweight <18.5 kg/m²; normal = [18.5-25.0[ kg/m²; overweight = [25.0-30.0[ kg/m²; obese ≥30.0 kg/m²). Exposures were lagged by 5 years in main analyses; we used longer lags (10 and 20 years) in sensitivity analyses. We examined trajectories of BMI categories within a nested case-control study using multivariable generalized estimating equations multinomial logistic models.

RESULTS

Of 96,702 women (baseline age = 40-65 years), 1,164 developed PD. PD incidence was lower (HR = 0.76, 95% CI = 0.59-0.98, p = 0.032) among women with obesity compared with those with normal BMI. There was a similar association in analyses using longer lag times (20 years, 598 cases, HR = 0.52, 95% CI = 0.30-0.88, p = 0.016). A similar pattern was seen for WC and waist-height ratio but not waist-hip ratio. Trajectories of BMI categories (1,196 patients and 23,876 controls) showed that obesity was less frequent in patients with PD before diagnosis than in controls, with a statistically significant difference 29 years before. In addition, the frequency of obesity decreased 5-10 years before diagnosis in patients.

DISCUSSION

In this large cohort of women with a long follow-up, obesity was associated with a lower hazard of PD, even when measured 20 years before diagnosis, in agreement with Mendelian randomization studies. Our analyses underscore the importance of lagged analyses to account for reverse causation. These findings warrant further investigations to understand the mechanisms underlying this inverse association.

The Effect of Blood Lipids, Type 2 Diabetes, and Body Mass Index on Parkinson's Disease: A Korean Mendelian Randomization Study

OBJECTIVE

Associations between various metabolic conditions and Parkinson's disease (PD) have been previously identified in epidemiological studies. We aimed to investigate the causal effect of lipid levels, type 2 diabetes mellitus (T2DM), and body mass index (BMI) on PD in a Korean population via Mendelian randomization (MR).

METHODS

Two-sample MR analyses were performed with inverse-variance weighted (IVW), weighted median, and MR-Egger regression approaches. We identified genetic variants associated with lipid concentrations, T2DM, and BMI in publicly available summary statistics, which were either collected from genome-wide association studies (GWASs) or from meta-analyses of GWAS that targeted only Korean individuals or East Asian individuals, including Korean individuals. The outcome dataset was a GWAS on PD performed in a Korean population.

RESULTS

From previous GWASs and meta-analyses, we selected single nucleotide polymorphisms as the instrumental variables. Variants associated with serum levels of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides, as well as with T2DM and BMI, were selected (n = 11, 19, 17, 89, and 9, respectively). There were no statistically significant causal associations observed between the five exposures and PD using either the IVW, weighted median, or MR-Egger methods (p-values of the IVW method: 0.332, 0.610, 0.634, 0.275, and 0.860, respectively).

CONCLUSION

This study does not support a clinically relevant causal effect of lipid levels, T2DM, and BMI on PD risk in a Korean population.

Machine learning based risk prediction for Parkinson's disease with nationwide health screening data

Although many studies have been conducted on machine learning (ML) models for Parkinson's disease (PD) prediction using neuroimaging and movement analyses, studies with large population-based datasets are limited. We aimed to propose PD prediction models using ML algorithms based on the National Health Insurance Service-Health Screening datasets. We selected individuals who participated in national health-screening programs > 5 times between 2002 and 2015. PD was defined based on the ICD-code (G20), and a matched cohort of individuals without PD was selected using a 1:1 random sampling method. Various ML algorithms were applied for PD prediction, and the performance of the prediction models was compared. Neural networks, gradient boosting machines, and random forest algorithms exhibited the best average prediction accuracy (average area under the receiver operating characteristic curve (AUC): 0.779, 0.766, and 0.731, respectively) among the algorithms validated in this study. The overall model performance metrics were higher in men than in women (AUC: 0.742 and 0.729, respectively). The most important factor for predicting PD occurrence was body mass index, followed by total cholesterol, glucose, hemoglobin, and blood pressure levels. Smoking and alcohol consumption (in men) and socioeconomic status, physical activity, and diabetes mellitus (in women) were highly correlated with the occurrence of PD. The proposed health-screening dataset-based PD prediction model using ML algorithms is readily applicable, produces validated results, and could be a useful option for PD prediction models.

Cerebral Blood Flow Alterations and Obesity: A Systematic Review and Meta-Analysis

Background: Reduction in cerebral blood flow (CBF) plays an essential role in the cognitive impairment and dementia in obesity. However, current conclusions regarding CBF changes in patients with obesity are inconsistent. Objective: A systematic review and meta-analysis was performed to evaluate the relationship between obesity and CBF alterations. Methods: We systematically screened published cross-sectional and longitudinal studies focusing on the differences in CBF between obese and normal-weight individuals. Eighteen studies including 24,866 participants, of which seven articles reported longitudinal results, were evaluated in the present study. Results: The results of the meta-analysis showed that in cross-sectional studies, body mass index (BMI) was negatively associated with CBF (β= –0.31, 95% confidence interval [CI]: –0.44, –0.19). Moreover, this systematic review demonstrated that obese individuals showed global and regional reductions in the CBF and increased CBF in diverse functional areas of the frontal lobe, including the prefrontal cortex, left frontal superior orbital, right frontal mid-orbital cortex, and left premotor superior frontal gyrus. Conclusion: Our findings suggest that BMI, rather than waist circumference and waist-to-hip ratio, is inversely associated with CBF in cross-sectional studies. The CBF of obese individuals showed global and regional reductions, including the frontal lobe, temporal and parietal lobes, cerebellum, hippocampus, and thalamus.

Clinical trajectories and biomarkers for weight variability in early Parkinson's disease

Unexplained weight changes that occur in Parkinson's disease (PD), are often neglected and remain a poorly understood non-motor feature in patients with PD. A specific 'Park-weight' phenotype with low body weight has been described, and our aim was to evaluate the clinical and prognostic trajectories and biomarkers of weight variability in PD. We evaluated body weight-related biomarkers in 405 de novo PD patients and 187 healthy controls (HC) over a 5-year follow-up period from the PPMI database. Body-weight variability was defined as intra-individual variability in body weight between visits. PD patients were categorized as weight losers, gainers, or patients with stable weight. The differential progression of motor and non-motor clinical variables between groups was explored using linear mixed-effects models. Finally, we estimated longitudinal changes in weight as a function of baseline and longitudinal striatal presynaptic dopaminergic transporter imaging. PD patients presented a greater weight variability compared to HC (p = 0.003). Patients who developed weight loss had lower CSF amyloid-beta 1-42 (p = 0.009) at baseline. In addition, patients with weight loss showed a faster cognitive decline (p = 0.001), whereas patients with weight gain showed a slower motor progression (p = 0.001), compared to patients with stable weight. Baseline right striatal denervation was a predictor of weight variability in both PD patients and HC (p < 0.001). Similarly, weight variability in PD patients was associated with the progression of right striatal denervation (p < 0.001). Weight variability and specifically weight loss are more frequent in PD compared to HC, and are associated with specific motor, non-motor and cognitive progression patterns. A greater CSF amyloid burden was present at baseline in patients with subsequent weight loss. Presynaptic dopaminergic imaging in the right striatum may serve as a predictor of future weight changes in PD and HC.

Life style and Parkinson's disease

The question whether life style may impair the advent or course of the disease in patients with Parkinsonism is of great importance for patients and physicians alike. We present here comprehensive information on the influence of the environment, diet (especially caffeine, nicotine, alcohol, chocolate and dairy products), physical activity and sleep on risk and course of Parkinson’s disease.

Association between statin use and Parkinson's disease in Korean patients with hyperlipidemia

INTRODUCTION

Findings on the association between statin therapy and Parkinson's disease (PD) occurrence have been inconsistent. This study aimed to identify the association between statin use and PD in participants with a history of hyperlipidemia or blood cholesterol >200 in a Korean population to exclude nonstatin users owing to normal lipid values.

METHODS

We conducted a nested case-control analysis using the Korean National Health Insurance Service-National Sample Cohort assessed between 2002 and 2015. We identified 3026 PD cases. A total of 12,104 controls were then individually matched by age, sex, income, and region of residence at a ratio of 1:4. Potential confounders comprised basic demographic factors, lifestyle factors, various medical conditions and comorbidities. A conditional/unconditional logistic regression method was applied.

RESULTS

Compared with statin use for <6 months, adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for 6-12 months of statin use and ≥12 months of statin use were 1.03 (0.92-1.15) and 1.61 (1.35-1.93) after adjustment for confounders, respectively (P = 0.664 and P < 0.001). In analyses according to statin solubility, only the association between lipophilic statin use for ≥12 months and PD maintained statistical significance, with an aOR of 1.64 (95% CI = 1.34-2.01, P < 0.001). These relations were consistent in subgroup analyses by covariates.

CONCLUSIONS

Statin use for more than 12 months was associated with a higher probability of PD in the Korean population with hyperlipidemia. This probability was significant for lipophilic statins but not hydrophilic statins.

Risk of Parkinson Disease and Secondary Parkinsonism in Myocardial Infarction Survivors

Background

In addition to primary neurodegenerative processes, vascular disorders, such as stroke, can lead to parkinsonism. However, some cardiovascular risk factors, such as smoking and elevated cholesterol levels, are associated with reduced risk of Parkinson disease. We examined the risk of Parkinson disease and secondary parkinsonism in 1‐year survivors of myocardial infarction (MI).

Methods and Results

We conducted a nationwide population‐based matched cohort study using Danish medical registries from 1995 to 2016. We identified all patients with a first‐time MI diagnosis and sampled a sex‐, age‐, and calendar year–matched general population comparison cohort without MI. Cox regression analysis was used to compute adjusted hazard ratios (aHRs) for Parkinson disease and secondary parkinsonism, controlled for matching factors and adjusted for relevant comorbidities and socioeconomic factors. We identified 181 994 patients with MI and 909 970 matched comparison cohort members (median age, 71 years; 62% men). After 21 years of follow‐up, the cumulative incidence was 0.9% for Parkinson disease and 0.1% for secondary parkinsonism in the MI cohort. Compared with the general population cohort, MI was associated with a decreased risk of Parkinson disease (aHR, 0.80; 95% CI, 0.73–0.87) and secondary parkinsonism (aHR, 0.72; 95% CI, 0.54–0.94).

Conclusions

MI was associated with a 20% decreased risk of Parkinson disease and 28% decreased risk of secondary parkinsonism. Reduced risk may reflect an inverse relationship between cardiovascular risk factors and Parkinson disease.

Associations Between Diabetic Retinopathy and Parkinson's Disease: Results From the Catalonian Primary Care Cohort Study

The purpose of this study was to assess the risk of occurrence of Parkinson's disease (PD) among subjects with type 2 diabetes and diabetic retinopathy (DR) in our large primary health care database from Catalonia (Spain). A retrospective cohort study with pseudo-anonymized routinely collected health data from SIDIAP was conducted from 2008 to 2016. We calculated the number of events, time to event, cumulative incidence, and incidence rates of PD for subjects with and without DR and for different stages of DR. The proportional hazards regression analysis was done to assess the probability of occurrence between DR and PD. In total, 26,453 type 2 diabetic subjects with DR were identified in the database, and 216,250 subjects without DR at inclusion. During the follow-up period, 1,748 PD events occurred. PD incidence rate and cumulative incidence were higher among subjects with DR (16.95 per 10,000 person-years and 0.83%, respectively). In the unadjusted analysis, subjects with DR were at 1.25 times higher risk (hazard ratio: 1.22, 95% confidence interval: 1.06; 1.41) of developing PD during the study period. However, we did not find any statistically significant HR for DR in any models after adjusting for different risk factors (age, sex, duration of diabetes, smoking, body mass index, glycosylated hemoglobin, comorbidities). In conclusion, in our primary health care population database, DR was not associated with an increased risk of PD after adjusting for different risk factors. In our retrospective cohort study, age, male sex, and diabetes duration were independent risk factors for developing PD.

Predicting Parkinson's Disease and Its Pathology via Simple Clinical Variables

Background:

Parkinson’s disease (PD) is a chronic, disabling neurodegenerative disorder.

Objective:

To predict a future diagnosis of PD using questionnaires and simple non-invasive clinical tests.

Methods:

Participants in the prospective Kuakini Honolulu-Asia Aging Study (HAAS) were evaluated biannually between 1995–2017 by PD experts using standard diagnostic criteria. Autopsies were sought on all deaths. We input simple clinical and risk factor variables into an ensemble-tree based machine learning algorithm and derived models to predict the probability of developing PD. We also investigated relationships of predictive models and neuropathologic features such as nigral neuron density.

Results:

The study sample included 292 subjects, 25 of whom developed PD within 3 years and 41 by 5 years. 116 (46%) of 251 subjects not diagnosed with PD underwent autopsy. Light Gradient Boosting Machine modeling of 12 predictors correctly classified a high proportion of individuals who developed PD within 3 years (area under the curve (AUC) 0.82, 95%CI 0.76–0.89) or 5 years (AUC 0.77, 95%CI 0.71–0.84). A large proportion of controls who were misclassified as PD had Lewy pathology at autopsy, including 79%of those who died within 3 years. PD probability estimates correlated inversely with nigral neuron density and were strongest in autopsies conducted within 3 years of index date (r = –0.57, p < 0.01).

Conclusion:

Machine learning can identify persons likely to develop PD during the prodromal period using questionnaires and simple non-invasive tests. Correlation with neuropathology suggests that true model accuracy may be considerably higher than estimates based solely on clinical diagnosis.

Effects of dietary restriction on neuroinflammation in neurodegenerative diseases

Recent and accumulating work in experimental animal models and humans shows that diet has a much more pervasive and prominent role than previously thought in modulating neuroinflammatory and neurodegenerative mechanisms leading to some of the most common chronic central nervous system (CNS) diseases. Chronic or intermittent food restriction has profound effects in shaping brain and peripheral metabolism, immunity, and gut microbiome biology. Interactions among calorie intake, meal frequency, diet quality, and the gut microbiome modulate specific metabolic and molecular pathways that regulate cellular, tissue, and organ homeostasis as well as inflammation during normal brain aging and CNS neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis, among others. This review discusses these findings and their potential application to the prevention and treatment of CNS neuroinflammatory diseases and the promotion of healthy brain aging.

Association between body weight variability and incidence of Parkinson disease: A nationwide, population-based cohort study

BACKGROUND AND PURPOSE

Although body weight variability has been associated with mortality, cardiovascular disease, and dementia, the relationship between body weight variability and Parkinson disease (PD) has rarely been studied. We aimed to investigate the longitudinal association between body weight variability and PD incidence.

METHODS

A nationwide population-based, cohort study was conducted using the database from the Health Insurance Review and Assessment Service of the whole Korean population. We analyzed 2,815,135 participants (≥40 years old, mean age = 51.7 ± 8.6 years, 66.8% men) without a previous PD diagnosis. We determined individual body weight variability from baseline weight and follow-up visits. We used Cox proportional hazards regression models.

RESULTS

The highest quartile group was associated with increased PD incidence compared with the lowest quartile group after adjustment for confounding factors (hazard ratio [HR] = 1.18, 95% confidence interval [CI] = 1.08-1.29). In contrast, baseline body mass index, baseline waist circumference, and waist circumference variability were not associated with increased PD incidence. In the body weight loss group, individuals within the quartile of the highest variation in body weight showed a higher HR of PD risk than those within other quartiles (HR = 1.41, 95% CI = 1.18-1.68).

CONCLUSIONS

Body weight variability, especially weight loss, was associated with higher PD incidence. This finding has important implications for clinicians and supports the need for preventative measures and surveillance for PD in individuals with fluctuating body weight.

Association of NO2 and Other Air Pollution Exposures With the Risk of Parkinson Disease

Importance

The development of Parkinson disease (PD) may be promoted by exposure to air pollution.

Objective

To investigate the potential association between exposure to particulate matters (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO) and the risk of incident PD.

Design, Setting, and Participants

This retrospective cohort study used data from the Korean National Health Insurance Service. Among the 1 021 208 Korean individuals in the database, those who had lived in Seoul from January 2002 to December 2006 (n = 176 875) were screened for eligibility. A total of 78 830 adults older than 40 years without PD and who lived in Seoul between January 2002 and December 2006 were included in this study. Individuals diagnosed with PD before 2006 (n = 159) and individuals 40 years or younger (n = 97 886) were excluded. Each participant was followed up with annually from January 2007 to December 2015, thereby adding up to 757 704 total person-years of follow-up. Data were analyzed from January to September 2020.

Exposures

Individual exposure levels to PM2.5, PM10, NO2, O3, SO2, and CO were estimated based on the participants' residential address at the district level. To evaluate long-term exposure to air pollution, time-varying 5-year mean air pollutant exposure was calculated for each participant.

Main Outcomes and Measures

The outcome measure was the association between air pollution and the risk of incident PD measured as hazard ratios after adjusting for demographic factors, socioeconomic factors, and medical comorbidities.

Results

At baseline, the mean (SD) age of the 78 830 participants was 54.4 (10.7) years, and 41 070 (52.1%) were female. A total of 338 individuals with newly diagnosed PD were identified during the study period. Exposure to NO2 was associated with an increase in risk of PD (hazard ratio for highest vs lowest quartile, 1.41; 95% CI, 1.02-1.95; P for trend = .045). No statistically significant associations between exposure to PM2.5, PM10, O3, SO2, or CO and PD incidence were found.

Conclusions and Relevance

In this large cohort study, a statistically significant association between NO2 exposure and PD risk was identified. This finding suggests the role of air pollutants in PD development, advocating for the need to implement a targeted public health policy.

Serum lipid profile of Parkinson's disease patients: A study from the Northwest of Iran

BACKGROUND

Parkinson's disease (PD) is defined as a long-lasting, neurological illness. Low levels of serum lipid fractions are related with a high risk of PD. Current investigation was designed to evaluate the concentration blood lipid fractions in patients suffering from PD and compared with healthy subjects.

METHODS

This case-control study was conducted from February 2016 to September 2018 in Tabriz University of Medical Sciences, Tabriz, Iran. The present investigation consisted of 75 persons who had PD and 75 normal people. The blood levels of lipid fractions were measured by concentrations of total cholesterol (TC), serum triglycerides (TG), low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C), and total cholesterol. The results were analyzed with SPSS software using Kolmogorov-Smirnov, chi-square, and student's t-test.

RESULTS

Serum level of TG was remarkably lower in patients with PD (111.92±8.75 mg/dL) compared with healthy subjects (123.64±9.97 mg/dL, P=0.008). Furthermore, we saw an important difference in the level of LDL-C (P=0.001) and TC (P=0.004) between the two groups. However, there was not any observed meaningful difference in the serum concentrations of HDL-C between the studied groups (P=0.135).

CONCLUSION

Our results showed that the serum concentration of TG, LDL-C, and TC are noticeably lower in the PD suffering patients. Further investigations are needed to provide comprehensive information on the participants' cognitive layout and subsequent actions.

Body Mass Index Is Significantly Associated With Disease Severity in Spinocerebellar Ataxia Type 2 Patients

BACKGROUND

Spinocerebellar ataxia type 2 is a progressive neurodegenerative disorder due to an unstable expansion of a CAG repeat in the ATXN2 gene. Although weight loss has been associated with disease progression in several neurodegenerative conditions, it has been barely assessed in patients with spinocerebellar ataxia type 2.

OBJECTIVE

The objective of this study was to test whether body mass index is altered in patients with spinocerebellar ataxia type 2 with varying expansion sizes from early to late disease stages.

METHODS

A cross-sectional case-control study was performed, which included 222 clinically and molecularly diagnosed patients and 214 sex- and age-matched healthy individuals. ATXN2 genotypes and sex were considered as risk factors. Clinical outcomes included the body mass index, age at onset, disease duration, Scale for the Assessment and Rating of Ataxia score, disease stage, dysphagia, and progression rate. Multiple linear regression models were generated.

RESULTS

Body mass index was significantly decreased in male patients, but not in female patients, relative to control subjects. In addition to sex, body mass index was significantly associated with age at onset and progression rate. Conversely, body mass index, along with repeat length in ATXN2 expanded alleles and disease duration, was associated with Scale for the Assessment and Rating of Ataxia score. In addition, body mass index, along with the age at onset and the repeat length in ATXN2 normal and expanded alleles, has a significant influence on progression rate.

CONCLUSIONS

Body mass index might be a useful biomarker of disease severity, particularly in male patients with spinocerebellar ataxia type 2 in the context of nutritional interventions or clinical trials assessing the efficacy of promising new drugs. © 2021 International Parkinson and Movement Disorder Society.

Dietary Antioxidants and the Risk of Parkinson Disease: The Swedish National March Cohort

OBJECTIVE

To determine whether high baseline dietary antioxidants and total nonenzymatic antioxidant capacity (NEAC) is associated with a lower risk of Parkinson disease (PD) in men and women, we prospectively studied 43,865 men and women from a large Swedish cohort.

METHODS

In the Swedish National March Cohort, 43,865 men and women aged 18-94 years were followed through record linkages to National Health Registries from 1997 until 2016. Baseline dietary vitamin E, vitamin C, and beta-carotene intake, as well as NEAC, were assessed by a validated food frequency questionnaire collected at baseline. All exposure variables were adjusted for energy intake and categorized into tertiles. Multivariable Cox proportional hazard regression models were fitted to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for PD.

RESULTS

After a mean follow-up time of 17.6 years, we detected 465 incidence cases of PD. In the multivariable adjusted model, dietary vitamin E (HR 0.68, 95% CI 0.52-0.90; p for trend 0.005) and vitamin C (HR 0.68, 95% CI 0.52-0.89; p for trend 0.004) were inversely associated with the risk of PD when comparing participants in the highest vs the lowest tertiles of exposure. No association was found with estimated intake of dietary beta-carotene or NEAC.

CONCLUSION

Our findings suggest that dietary vitamin E and C intake might be inversely associated with the risk of PD. No association was found with dietary beta-carotene or NEAC.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that dietary vitamin E and C intake are inversely associated with the risk of PD.

Cholesterol metabolism and brain injury in neonatal encephalopathy

Neonatal encephalopathy (NE) results from impaired cerebral blood flow and oxygen delivery to the brain. The pathophysiology of NE is complex and our understanding of its underlying pathways continues to evolve. There is considerable evidence that cholesterol dysregulation is involved in several adult diseases, including traumatic brain injury, stroke, Huntington's disease, and Parkinson's disease. Although the research is less robust in pediatrics, there is emerging evidence that aberrations in cholesterol metabolism may also be involved in the pathophysiology of neonatal NE. This narrative review provides an overview of cholesterol metabolism in the brain along with several examples from the adult literature where pathologic alterations in cholesterol metabolism have been associated with inflammatory and ischemic brain injury. Using those data as a background, the review then discusses the current preclinical data supporting the involvement of cholesterol in the pathogenesis of NE as well as how brain-specific cholesterol metabolites may serve as serum biomarkers for brain injury. Lastly, we review the potential for using the cholesterol metabolic pathways as therapeutic targets. Further investigation of the shifts in cholesterol synthesis and metabolism after hypoxia-ischemia may prove vital in understanding NE pathophysiology as well as providing opportunities for rapid diagnosis and therapeutic interventions. IMPACT: This review summarizes emerging evidence that aberrations in cholesterol metabolism may be involved in the pathophysiology of NE. Using data from NE as well as analogous adult disease states, this article reviews the potential for using cholesterol pathways as targets for developing novel therapeutic interventions and using cholesterol metabolites as biomarkers for injury. When possible, gaps in the current literature were identified to aid in the development of future studies to further investigate the interactions between cholesterol pathways and NE.

[Neuroendocrine and metabolic impairments in patients with Parkinson's disease]

ABSRACT

Neuroendocrine and neurometabolic disorders, although occasionally noted in Parkinson's disease (PD), existed in the shadow of motor and non-motor symptoms (hypokinesia, rigidity, tremor, depression, constipation, etc.). In recent years, they are increasingly being diagnosed and are the subject of special research. These include, in particular, disorders of carbohydrate metabolism, changes in body weight, metabolic disorders in bone tissue, secretion, as well as the secretion of neurohormones, such as melatonin. They are associated with other non-motor symptoms, negatively affect patients' general condition and quality of life, but can be treatable. At the same time, treatment of neuroendocrine and neurometabolic disorders can favorably influence the rate of progression of the disease as a whole. This review discusses the pathophysiological mechanisms, clinical consequences, as well as pharmacological and non-pharmacological approaches to the treatment of neuroendocrine and neurometabolic disorders arising in PD, which have been relatively rarely covered in literature.

Diet, Microbiota and Brain Health: Unraveling the Network Intersecting Metabolism and Neurodegeneration

Increasing evidence gives support for the idea that extra-neuronal factors may affect brain physiology and its predisposition to neurodegenerative diseases. Epidemiological and experimental studies show that nutrition and metabolic disorders such as obesity and type 2 diabetes increase the risk of Alzheimer's and Parkinson's diseases after midlife, while the relationship with amyotrophic lateral sclerosis is uncertain, but suggests a protective effect of features of metabolic syndrome. The microbiota has recently emerged as a novel factor engaging strong interactions with neurons and glia, deeply affecting their function and behavior in these diseases. In particular, recent evidence suggested that gut microbes are involved in the seeding of prion-like proteins and their spreading to the central nervous system. Here, we present a comprehensive review of the impact of metabolism, diet and microbiota in neurodegeneration, by affecting simultaneously several aspects of health regarding energy metabolism, immune system and neuronal function. Advancing technologies may allow researchers in the future to improve investigations in these fields, allowing the buildup of population-based preventive interventions and development of targeted therapeutics to halt progressive neurologic disability.

Metabolic Syndrome and Parkinson's Disease Incidence: A Nationwide Study Using Propensity Score Matching

Background: Metabolic syndrome (MetS) and Parkinson's disease (PD) share common pathophysiological mechanisms. This study aimed to investigate the influence of MetS on PD incidence. Materials and Methods: A propensity score-matched cohort study was conducted using the National Health Insurance Service-National Health Screening Cohort (NHIS-HealS) data (2002-2015) from the Korean National Health Insurance Service. Individuals with MetS were identified from those who underwent a health checkup in 2009-2010 and were 1:1 matched to individuals without MetS (non-MetS) using the propensity score method. Among 314,737 eligible individuals, 85,530 MetS and non-MetS pairs were selected. Results: During a mean follow-up of 7.23 years, 819 (0.48%) PD cases occurred. Individuals with MetS exhibited 1.23 times greater PD incidence (95% confidence interval [CI], 1.06-1.43; P = 0.006). The risk of PD increased with the number of MetS components, with the presence of five MetS components altogether doubling the incidence of PD (odds ratio [OR], 2.00; 95% CI, 1.30-3.04; P = 0.001). High blood pressure, low high-density lipoprotein cholesterol, and high fasting blood glucose increased PD incidence by 1.34 times (95% CI, 1.15-1.58; P < 0.001), 1.31 times (95% CI, 1.13-1.52; P < 0.001), and 1.20 times (95% CI, 1.04-1.38; P = 0.013), respectively. Elevated waist circumference was not associated with PD incidence (OR, 1.11; 95% CI, 0.96-1.28; P = 0.176). High triglycerides exerted a protective effect against PD incidence especially in men (OR, 0.66; 95% CI, 0.54-0.81; P < 0.001). Conclusions: MetS may be a risk factor for PD incidence, and individual components of MetS exert different effects depending on sex.

Visual Acuity and Development of Parkinson's Disease: A Nationwide Cohort Study

BACKGROUND

Visual dysfunction in Parkinson's disease (PD) is well known from previous reports, but the association of visual deficits with PD development has not yet been studied. The aim of this research was to evaluate the association of visual acuity with the risk of PD occurrence using a nationwide cohort in South Korea.

METHODS

Among the population participating in the National Health Insurance Service, which is mandatory for all South Koreans, 6,055,113 individuals who had taken part in health screening programs between January 1, 2009, and December 31, 2012, were included in the cohort and followed until December 31, 2017. The hazard ratio was calculated for groups with high and low visual acuity using multivariate adjusted Cox regression analysis.

RESULTS

A total of 22,872 subjects (0.38%) were diagnosed as having PD within the study period. Groups with low visual acuity showed a higher incidence of PD compared with groups with good visual acuity. Compared with the reference group (visual acuity better than 20/20), the adjusted hazard ratios and 95% confidence intervals (CIs) was 1.315 (95% CI, 1.261-1.371) for the group with visual acuity between 20/20 and 20/60, 1.357 (95% CI, 1.277-1.442) for the group with visual acuity between 20/60 and 10/100, and 1.267 (95% CI, 1.193-1.343) for the group with visual acuity less than 10/100.

CONCLUSIONS

Low visual acuity was associated with the development of PD. This suggests that visual dysfunction is one of the premotor symptoms for PD development. © 2020 International Parkinson and Movement Disorder Society.

Dietary Amino Acids Impact LRRK2-Induced Neurodegeneration in Parkinson's Disease Models

The G2019S mutation in leucine-rich repeat kinase 2 (LRRK2) is a common cause of Parkinson's disease (PD) and results in age-related dopamine neuron loss and locomotor dysfunction in Drosophila melanogaster through an aberrant increase in bulk neuronal protein synthesis. Under nonpathologic conditions, protein synthesis is tightly controlled by metabolic regulation. Whether nutritional and metabolic influences on protein synthesis can modulate the pathogenic effect of LRRK2 on protein synthesis and thereby impact neuronal loss is a key unresolved question. Here, we show that LRRK2 G2019S-induced neurodegeneration is critically dependent on dietary amino acid content in Drosophila studies with both sexes. Low dietary amino acid concentration prevents aberrant protein synthesis and blocks LRRK2 G2019S-mediated neurodegeneration in Drosophila and rat primary neurons. Unexpectedly, a moderately high-amino acid diet also blocks dopamine neuron loss and motor deficits in Drosophila through a separate mechanism involving stress-responsive activation of 5'-AMP-activated protein kinase (AMPK) and neuroprotective induction of autophagy, implicating the importance of protein homeostasis to neuronal viability. At the highest amino acid diet of the range tested, PD-related neurodegeneration occurs in an age-related manner, but is also observed in control strains, suggesting that it is independent of mutant LRRK2 expression. We propose that dietary influences on protein synthesis and autophagy are critical determinants of LRRK2 neurodegeneration, opening up possibilities for future therapeutic intervention.SIGNIFICANCE STATEMENT Parkinson's disease (PD) prevalence is projected to rise as populations continue to age, yet there are no current therapeutic approaches that delay or stop disease progression. A broad role for leucine-rich repeat kinase 2 (LRRK2) mutations in familial and idiopathic PD has emerged. Here, we show that dietary amino acids are important determinants of neurodegeneration in a Drosophila model of LRRK2 PD. Restricting all amino acids effectively suppresses dopaminergic neuron loss and locomotor deficits and is associated with reduced protein synthesis, while moderately high amino acids similarly attenuate these PD-related phenotypes through a stress-responsive induction of 5'-AMP-activated protein kinase and autophagy. These studies suggest that diet plays an important role in the development of PD-related phenotypes linked to LRRK2.

Effects of Higher Serum Lipid Levels on the Risk of Parkinson's Disease: A Systematic Review and Meta-Analysis

Background: The causal relationship between serum lipid levels and the risk of Parkinson's disease (PD) remains largely uncertain. We summarized the existing controversial evidence on this topic.

Methods: We searched the electronic databases for observational studies from January 1988 to March 2020. We applied random-effects models to calculate pooled relative risk (RR) with their 95% confidence intervals (CI). Random-effects dose-response meta-analyses were further conducted to explore the dose-risk relationship.

Results: Twelve cohort studies and three case-control studies were included in this meta-analysis. Higher levels of serum low-density lipoprotein cholesterol (LDL-C) were inversely associated with the subsequent risk of PD (RR 0.73, 95% CI 0.57–0.93), whereas, there were no associations between serum levels of total cholesterol (TC) (RR 0.91, 95% CI 0.73–1.13), high-density lipoprotein cholesterol (HDL-C) (RR 0.97, 95% CI 0.73–1.27), or triglycerides (TG) (RR 0.85, 95% CI 0.55–1.29) and the risk of PD. Further dose-response meta-analysis revealed that every 38.6 mg/dL (1mmol/L) increase in serum LDL-C correlates with a 7% decreased risk of PD.

Conclusions: Our paper supports the protective effect of higher serum LDL-C on the subsequent risk of PD. More prospective cohort studies are warranted to confirm the conclusion, and further fundamental researches are needed to elucidate the underlying biological mechanisms.

Metabolic syndrome does not influence the phenotype of LRRK2 and GBA related Parkinson's disease

In order toevaluate the influence of the metabolic syndrome (MS) (obesity, hypertension, elevated triglycerides, reduced levels of HDL cholesterol and glucose impairment) on the phenotype of LRRK2 and GBA Parkinson’s disease (PD), and on the prevalence of prodromal features among individuals at risk, we collected, laboratory test results, blood pressure, demographic, cognitive, motor, olfactory and affective information enabling the assessment of each component of MS and the construction of the MDS prodromal probability score. The number of metabolic components and their levels were compared between participants who were separated based on disease state and genetic status. One hundred and four idiopathic PD, 40 LRRK2-PD, 70 GBA-PD, 196 healthy non-carriers, 55 LRRK2-NMC and 97 GBA-NMC participated in this study. PD groups and non manifesting carriers (NMC) did not differ in the number of metabolic components (p = 0.101, p = 0.685, respectively). LRRK2-PD had higher levels of triglycerides (p = 0.015) and higher rates of prediabetes (p = 0.004), while LRRK2-NMC had higher triglyceride levels (p = 0.014). NMC with probability rates for prodromal PD above 50% had higher frequencies of hypertriglyceridemia and prediabetes (p < 0.005, p = 0.023 respectively). While elevated triglycerides and prediabetes were more frequent among LRRK2 carriers, MS does not seem to influence GBA and LRRK2-PD phenotype.

Association of body mass index with longitudinal rates of retinal atrophy in multiple sclerosis

BACKGROUND

Studies evaluating associations between body mass index (BMI) and optical coherence tomography (OCT) measures in multiple sclerosis (MS) are lacking.

OBJECTIVE

To assess whether elevated BMI is associated with accelerated retinal atrophy.

METHODS

In this observational study, 513 MS patients were followed with serial spectral-domain OCT for a median of 4.4 years. Participants were categorized as normal weight (BMI: 18.5-24.9 kg/m²), overweight (BMI: 25-29.9 kg/m²), and obese (BMI: ⩾30 kg/m²). Participants with diabetes mellitus or uncontrolled hypertension and eyes with optic neuritis (ON) ⩽6 months prior to baseline OCT or during follow-up were excluded. Statistical analyses were performed with mixed-effects linear regression.

RESULTS

Obese patients (n = 146) exhibited accelerated rates of ganglion cell + inner plexiform layer (GCIPL) atrophy relative to normal weight patients (n = 214; -0.57%/year (95% confidence interval (CI): -0.65% to -0.48%) versus -0.42%/year (95% CI: -0.49% to -0.35%); p = 0.012). GCIPL atrophy rate did not differ between overweight (n = 153) and normal weight patients (-0.47%/year vs -0.42%/year; p = 0.41). Each 1 kg/m² higher BMI was associated with accelerated GCIPL (-0.011%/year; 95% CI: -0.019% to -0.004%; p = 0.003) atrophy. Multivariable analyses accounting for age, sex, race, MS subtype, and ON history did not alter the above findings.

CONCLUSIONS

Elevated BMI, in the absence of overt metabolic comorbidities, may be associated with accelerated GCIPL atrophy. Obesity, a modifiable risk factor, may be associated with accelerated neurodegeneration in MS.

What and How Can Physical Activity Prevention Function on Parkinson's Disease?

Aim

This study was aimed at investigating the effects and molecular mechanisms of physical activity intervention on Parkinson's disease (PD) and providing theoretical guidance for the prevention and treatment of PD.

Methods

Four electronic databases up to December 2019 were searched (PubMed, Springer, Elsevier, and Wiley database), 176 articles were selected. Literature data were analyzed by the logic analysis method.

Results

(1) Risk factors of PD include dairy products, pesticides, traumatic brain injury, and obesity. Protective factors include alcohol, tobacco, coffee, black tea, and physical activity. (2) Physical activity can reduce the risk and improve symptoms of PD and the beneficial forms of physical activity, including running, dancing, traditional Chinese martial arts, yoga, and weight training. (3) Different forms of physical activity alleviate the symptoms of PD through different mechanisms, including reducing the accumulation of α-syn protein, inflammation, and oxidative stress, while enhancing BDNF activity, nerve regeneration, and mitochondrial function.

Conclusion

Physical activity has a positive impact on the prevention and treatment of PD. Illustrating the molecular mechanism of physical activity-induced protective effect on PD is an urgent need for improving the efficacy of PD therapy regimens in the future.

Body mass index, diabetes, and the risk of Parkinson's disease

BACKGROUND

There are conflicting findings in the literature regarding the association of body mass index and incidence of PD.

OBJECTIVES

This study aimed to investigate the association of body mass index with the risk of PD incidence while considering diabetes mellitus as a major confounding factor.

METHODS

We examined 6,800,601 individuals (aged ≥40 years) who were free of PD using the database of the Korean National Health Insurance Service. Cox proportional hazard regression was used to assess adjusted hazard ratios for PD with adjustment for potential confounders. Stratified analyses by diabetes status were also performed.

RESULTS

A total of 33,443 individuals were diagnosed with PD during the follow-up period (7.3 years). An increased risk of PD incidence was observed in the underweight group versus the normal group (adjusted hazard ratio: 1.28; 95% confidence interval: 1.21-1.36), whereas a decreased risk of PD incidence was observed (adjusted hazard ratio: 0.88; 95% confidence interval: 0.88-0.93) in the obese group and (adjusted hazard ratio: 0.77; 95% confidence interval: 0.72-0.82) in the severely obese group. This association consistently persisted after stratification by diabetes mellitus status, with the steepest downward slope for PD risk present with increasing body mass index in patients with severe diabetes mellitus (i.e., long duration or complication).

CONCLUSIONS

Being underweight and diabetes mellitus were associated with an increased risk of PD incidence, and effect of being underweight was more prominent in those with diabetes mellitus, with a dose-response relationship existing according to diabetes mellitus status. Further research is warranted to understand the clinical implications of the significant interaction between being underweight and diabetes mellitus status in the development of PD. © 2020 International Parkinson and Movement Disorder Society.

Protective Effects of the Caffeine Against Neurodegenerative Diseases

Background:

Recent studies and increased interest of the scientific community helped to clarify the neurological health property of caffeine, one of the pharmacologically active substances most consumed in the world.

Methods:

This article is a review search to provide an overview on the current state of understanding neurobiochemical impact of caffeine, focusing on the ability of the drug to effectively counteract several neurodegenerative disorders such as Alzheimer’s, Parkinson’s, Huntington’s diseases, Multiple sclerosis and Amyotrophic lateral sclerosis.

Results:

Data collection shown in this review provide a significant therapeutic and prophylactic potentiality of caffeine which acts on human brain through several pathways because of its antioxidant activity combined with multiple molecular targets. However, the need to adjust the CF dosage to individuals, because some people are more sensitive to drugs than others, may constituted a limit to the CF effectiveness.

Conclusion:

What emerges from the complex of clinical and epidemiological studies is a significant CF potential impact against all neurological disorders. Although, further studies are needed to fully elucidate the several mechanisms of drug action which in part are still elusive.

Genetic and Environmental Factors Contributing to Parkinson's Disease: A Case-Control Study in the Cypriot Population

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder affecting a substantial proportion of the elderly Cypriot population. The objective of this study was to evaluate PD risk variants that have been identified previously in Genome Wide Association Studies (GWAS) and to find environmental factors that are predictors for PD onset in the Cypriot population.

Methods: A case-control study was conducted with a total of 235 PD patients and 464 healthy controls of Greek-Cypriot ethnicity. Demographic and lifestyle characteristics, exposure to PD risk factors and clinical data were collected. Moreover, 13 previously GWAS-identified PD risk variants were genotyped. Univariate and multivariate regression analyses examined the association between a number of environmental and genetic factors and PD.

Results: Multivariable regression analysis revealed that exposure to both pesticides and other toxic substances (P = 0.03), severe head injury accompanied with fainting (P = 0.001), nuts consumption (P = 0.004), red meat consumption (P = 0.02), and soft drinks consumption (P = 0.008) were increasing the risk for PD, whereas cumulative smoking (P = 0.02), and fish consumption (P = 0.02) were decreasing the risk for PD. Five out of the 13 tested SNPs (rs12185268, rs6599389, rs356220, rs13312, and rs17649553) were confirmed to be nominally significantly associated (P < 0.05) with PD risk in the Cypriot population.

Conclusions: Collectively, this case-control study has shed some light on the nature of PD epidemiology in Cyprus, by demonstrating a number of genetic and environmental determinants of PD in the Cypriot population.

Associations between cerebrovascular risk factors and parkinson disease

OBJECTIVE

To determine whether cerebrovascular risk factors are associated with subsequent diagnoses of Parkinson disease, and whether these associations are similar in magnitude to those with subsequent diagnoses of Alzheimer disease.

METHODS

This was a retrospective cohort study using claims data from a 5% random sample of Medicare beneficiaries from 2008 to 2015. The exposures were stroke, atrial fibrillation, coronary disease, hyperlipidemia, hypertension, sleep apnea, diabetes mellitus, heart failure, peripheral vascular disease, chronic kidney disease, chronic obstructive pulmonary disease, valvular heart disease, tobacco use, and alcohol abuse. The primary outcome was a new diagnosis of idiopathic Parkinson disease. The secondary outcome was a new diagnosis of Alzheimer disease. Marginal structural Cox models adjusting for time-dependent confounding were used to characterize the association between exposures and outcomes. We also evaluated the association between cerebrovascular risk factors and subsequent renal colic (negative control).

RESULTS

Among 1,035,536 Medicare beneficiaries followed for a mean of 5.2 years, 15,531 (1.5%) participants were diagnosed with Parkinson disease and 81,974 (7.9%) were diagnosed with Alzheimer disease. Most evaluated cerebrovascular risk factors, including prior stroke (hazard ratio = 1.55; 95% confidence interval = 1.39-1.72), were associated with the subsequent diagnosis of Parkinson disease. The magnitudes of these associations were similar, but attenuated, to the associations between cerebrovascular risk factors and Alzheimer disease. Confirming the validity of our analytical model, most cerebrovascular risk factors were not associated with the subsequent diagnosis of renal colic.

INTERPRETATION

Cerebrovascular risk factors are associated with Parkinson disease, an effect comparable to their association with Alzheimer disease. ANN NEUROL 2019;86:572-581.

Uses for humanised mouse models in precision medicine for neurodegenerative disease

Neurodegenerative disease encompasses a wide range of disorders afflicting the central and peripheral nervous systems and is a major unmet biomedical need of our time. There are very limited treatments, and no cures, for most of these diseases, including Alzheimer's Disease, Parkinson's Disease, Huntington Disease, and Motor Neuron Diseases. Mouse and other animal models provide hope by analysing them to understand pathogenic mechanisms, to identify drug targets, and to develop gene therapies and stem cell therapies. However, despite many decades of research, virtually no new treatments have reached the clinic. Increasingly, it is apparent that human heterogeneity within clinically defined neurodegenerative disorders, and between patients with the same genetic mutations, significantly impacts disease presentation and, potentially, therapeutic efficacy. Therefore, stratifying patients according to genetics, lifestyle, disease presentation, ethnicity, and other parameters may hold the key to bringing effective therapies from the bench to the clinic. Here, we discuss genetic and cellular humanised mouse models, and how they help in defining the genetic and environmental parameters associated with neurodegenerative disease, and so help in developing effective precision medicine strategies for future healthcare.

Body Mass Index in Multiple Sclerosis modulates ceramide-induced DNA methylation and disease course

BACKGROUND

Multiple Sclerosis (MS) results from genetic predisposition and environmental variables, including elevated Body Mass Index (BMI) in early life. This study addresses the effect of BMI on the epigenome of monocytes and disease course in MS.

METHODS

Fifty-four therapy-naive Relapsing Remitting (RR) MS patients with high and normal BMI received clinical and MRI evaluation. Blood samples were immunophenotyped, and processed for unbiased plasma lipidomic profiling and genome-wide DNA methylation analysis of circulating monocytes. The main findings at baseline were validated in an independent cohort of 91 therapy-naïve RRMS patients. Disease course was evaluated by a two-year longitudinal follow up and mechanistic hypotheses tested in human cell cultures and in animal models of MS.

FINDINGS

Higher monocytic counts and plasma ceramides, and hypermethylation of genes involved in negative regulation of cell proliferation were detected in the high BMI group of MS patients compared to normal BMI. Ceramide treatment of monocytic cell cultures increased proliferation in a dose-dependent manner and was prevented by DNA methylation inhibitors. The high BMI group of MS patients showed a negative correlation between monocytic counts and brain volume. Those subjects at a two-year follow-up showed increased T1 lesion load, increased disease activity, and worsened clinical disability. Lastly, the relationship between body weight, monocytic infiltration, DNA methylation and disease course was validated in mouse models of MS.

INTERPRETATION

High BMI negatively impacts disease course in Multiple Sclerosis by modulating monocyte cell number through ceramide-induced DNA methylation of anti-proliferative genes. FUND: This work was supported by funds from the Friedman Brain Institute, NIH, and Multiple Sclerosis Society.

General and abdominal adiposity and the risk of Parkinson's disease: A prospective cohort study

INTRODUCTION

Due to demographic change, an increase in the frequency of Parkinson's disease (PD) patients is expected in the future and, thus, the identification of modifiable risk factors is urgently needed. We aimed to examine the associations of body mass index (BMI) and waist circumference (WC) with incident PD.

METHODS

In 13 of the 23 centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a total of 734 incident cases of PD were identified between 1992 and 2012 with a mean follow-up of 12 years. Cox proportional hazards regression was used to calculate hazard ratios (HR) with 95% confidence intervals (CI). We modelled anthropometric variables as continuous and categorical exposures and performed subgroup analyses by potential effect modifiers including sex and smoking.

RESULTS

We found no association between BMI, WC and incident PD, neither among men nor among women. Among never and former smokers, BMI and waist circumference were also not associated with PD risk. For male smokers, however, we observed a statistically significant inverse association between BMI and PD risk (HR 0.51, 95%CI: 0.30, 0.84) and the opposite for women, i.e. a significant direct association of BMI (HR 1.79, 95%CI: 1.04, 3.08) and waist circumference (HR 1.64, 95%CI: 1.03, 2.61) with risk of PD.

CONCLUSION

Our data revealed no association between excess weight and PD risk but a possible interaction between anthropometry, sex and smoking.

Cardiovascular risk factors and Parkinson's disease in 500,000 Chinese adults

OBJECTIVE

The objectives of this study were to compare the risks of Parkinson's disease among those with versus those without prior stroke or heart disease at baseline in a prospective study of 0.5 million adults in China, and to examine associations of cardiovascular disease risk factors (cigarette smoking, hypertension, diabetes, obesity) with risk of Parkinson's disease.

METHODS

During an average of 11.5 years of follow-up of 503,497 middle-aged participants in the China Kadoorie Biobank study, 603 incident cases were hospitalized with a diagnosis of Parkinson's disease. Cox proportional hazards models were used to assess associations of history of heart disease or stroke with Parkinson's disease in all participants, and of cardiovascular disease risk factors with Parkinson's disease in a subset without prior cardiovascular disease.

RESULTS

In this population the incidence rate of Parkinson's disease (mean [SD] age of cases, 61 [10] years) was 13.3 (95% confidence interval: 12.3-14.4) per 100,000 person-years. Incidence increased with age, and was higher in men than in women, and in urban than in rural residents. Prior stroke was associated with about twofold higher risk of Parkinson's disease (hazard ratio 1.94; 1.39-2.69). After adjustment for confounders in those without prior cardiovascular disease, a 5 kg/m2 higher body mass index was associated with 17% (1.17; 1.03-1.34: P = 0.019) higher risk of Parkinson's disease, but neither hypertension, diabetes, nor current cigarette smoking was significantly associated with Parkinson's disease.

INTERPRETATION

Prior stroke and adiposity were each associated with higher risks of Parkinson's disease, but none of the other cardiovascular disease risk factors were significantly associated with Parkinson's disease in this population.

Nrf2/ARE Pathway Modulation by Dietary Energy Regulation in Neurological Disorders

Nuclear factor erythroid 2-related factor 2 (Nrf2) regulates the expression of an array of enzymes with important detoxifying and antioxidant functions. Current findings support the role of high levels of oxidative stress in the pathogenesis of neurological disorders. Given the central role played by Nrf2 in counteracting oxidative damage, a number of studies have targeted the modulation of this transcription factor in order to confer neuroprotection. Nrf2 activity is tightly regulated by oxidative stress and energy-based stimuli. Thus, many dietary interventions based on energy intake regulation, such as dietary energy restriction (DER) or high-fat diet (HFD), modulate Nrf2 with consequences for a variety of cellular processes that affect brain health. DER, by either restricting calorie intake or meal frequency, activates Nrf2 thereby triggering its protective effects, whilst HFD inhibit this pathway, thereby exacerbating oxidative stress. Consequently, DER protocols can be valuable strategies in the management of central nervous system (CNS) disorders. Herein, we review current knowledge of the role of Nrf2 signaling in neurological diseases, namely Alzheimer’s disease, Parkinson’s disease, multiple sclerosis and cerebral ischemia, as well as the potential of energy intake regulation in the management of Nrf2 signaling.

The Impact of Ghrelin on the Survival and Efficacy of Dopaminergic Fetal Grafts in the 6-OHDA-Lesioned Rat

Ghrelin is a peptide produced in the gut with a wide range of physiological functions. Recent studies have suggested it may have potential as a neuroprotective agent in models of Parkinson's disease, reducing the impact of toxic challenges on the survival of nigral dopaminergic neurons. The presence of the ghrelin receptor (GHSR1a) on the dopaminergic neurons of the substantia nigra raises the possibility that a potential application for this property of ghrelin may be as an adjunctive neuroprotective agent to enhance and support the survival and integration of dopaminergic cells transplanted into the striatum. Thus far, inconsistent outcomes in clinical trials for fetal cell transplantation have been linked to low rates of cell survival which we hypothesize could be ameliorated by the presence of ghrelin. To explore this, we confirmed the expression of the GHSR1a and related enzymes on e14 ventral mesencephalon. To determine a functional effect, five groups of female Sprague-Dawley rats received a unilateral 6-OHDA lesion to the medial forebrain bundle and four received an intrastriatal graft of e14 ventral mesencephalic cells. Grafted rats received saline; acyl-ghrelin (10 µg/kg); acyl-ghrelin (50 µg/kg) or the ghrelin agonist JMV-2894 (160 µg/kg) i.p. for 8 weeks. An effect of ghrelin at low dose on hippocampal neurogenesis indicated blood-brain barrier penetrance and attainment of biologically relevant levels but neither acyl-ghrelin nor JMV-2894 improved graft survival or efficacy.